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Explore What Others Are Building

Here is a sample of public Insights made by Insight Maker users. This list is auto-generated and updated daily.

A spatially aware, agent based model of disease spread. There are three classes of people: susceptible (healthy), infected (sick and infectious), and recovered (healthy and temporarily immune). @ LinkedIn ,  Twitter ,  YouTube
ABM Disease SIR Roam

A spatially aware, agent based model of disease spread. There are three classes of people: susceptible (healthy), infected (sick and infectious), and recovered (healthy and temporarily immune).

@LinkedIn, Twitter, YouTube

Spatially Aware SIR Disease Model
Gene Bellinger
45
Based on Psychological Medicine Dec 2015  article   Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder by A. K. Wittenborn, H. Rahmandad, J. Rick and N. Hosseinichimeh, mentioned  here . See also 2018 N. Hosseinichimeh Plos ONE  article  for rumination focuss
The Body And Self Health Care Psychiatry Ability Emotion Stress Depression Behavior PCT Mental Health
Based on Psychological Medicine Dec 2015 article Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder by A. K. Wittenborn, H. Rahmandad, J. Rick and N. Hosseinichimeh, mentioned here. See also 2018 N. Hosseinichimeh Plos ONE article for rumination focussed SD simulation
Depression Dynamics
Geoff McDonnell
13
Active users slider: How many users do you start with at the beginning of your growth phase?  Acquisition, churn, and annual market growth rates are in percent (decimal). Market size is absolute in month 1.
Active users slider: How many users do you start with at the beginning of your growth phase? 
Acquisition, churn, and annual market growth rates are in percent (decimal). Market size is absolute in month 1.
non-OSS PJM tools pessimistic scenario - Logistic Growth with linear component (Organic Growth)
Marv van Pal
3 2 weeks ago
La situación modelada expresa el crecimiento de la cantidad de socios impulsadas por el aumento de costos competitivos y los precios accesibles, pero es frenada por la calidad de señal y el tiempo de resolución de reclamos, afectado por la capacidad técnica.
Arquetipo Sistémico
La situación modelada expresa el crecimiento de la cantidad de socios impulsadas por el aumento de costos competitivos y los precios accesibles, pero es frenada por la calidad de señal y el tiempo de resolución de reclamos, afectado por la capacidad técnica.
Límite de Crecimiento Cable TV - Grupo 7
Nico
5 days ago
SARS-CoV-19 spread  in different countries - please  adjust variables accordingly Italy elderly population (>65): 0.228 estimated undetected cases factor: 4-11 starting population size: 60 000 000 high blood pressure: 0.32 (gbe-bund) heart disease: 0.04 (statista) free intensive
Disease Coronavirus Infection Corona Virus COVID-19 SARS-CoV-19 Pandemic
SARS-CoV-19 spread in different countries
- please adjust variables accordingly

Italy
  • elderly population (>65): 0.228
  • estimated undetected cases factor: 4-11
  • starting population size: 60 000 000
  • high blood pressure: 0.32 (gbe-bund)
  • heart disease: 0.04 (statista)
  • free intensive care units: 3 100

Germany
  • elderly population (>65): 0.195 (bpb)
  • estimated undetected cases factor: 2-3 (deutschlandfunk)
  • starting population size: 83 000 000
  • high blood pressure: 0.26 (gbe-bund)
  • heart disease: 0.2-0.28 (herzstiftung)
  • free intensive care units: 5 880

France
  • elderly population (>65): 0.183 (statista)
  • estimated undetected cases factor: 3-5
  • starting population size: 67 000 000
  • high blood pressure: 0.3 (fondation-recherche-cardio-vasculaire)
  • heart disease: 0.1-0.2 (oecd)
  • free intensive care units: 3 000

As you wish
  • numbers of encounters/day: 1 = quarantine, 2-3 = practicing social distancing, 4-6 = heavy social life, 7-9 = not caring at all // default 2
  • practicing preventive measures (ie. washing hands regularly, not touching your face etc.): 0.1 (nobody does anything) - 1 (very strictly) // default 0.8
  • government elucidation: 0.1 (very bad) - 1 (highly transparent and educating) // default 0.9
  • Immunity rate (due to lacking data): 0 (you can't get immune) - 1 (once you had it you'll never get it again) // default 0.4

Key
  • Healthy: People are not infected with SARS-CoV-19 but could still get it
  • Infected: People have been infected and developed the disease COVID-19
  • Recovered: People just have recovered from COVID-19 and can't get it again in this stage
  • Dead: People died because of COVID-19
  • Immune: People got immune and can't get the disease again
  • Critical recovery percentage: Chance of survival with no special medical treatment
SARS-CoV-19 model
Lucia Vega Resto
56
The SEIRS(D) model for the purpose of experimenting with the phenomena of viral spread. I use it for COVID-19 simulation.
COVID-19 Coronavirus
The SEIRS(D) model for the purpose of experimenting with the phenomena of viral spread. I use it for COVID-19 simulation.
SEIR - COVID-19 (v.1)
Remigiusz Kinas
47